Join us at the first KTH AI (Society) Summit! In this event, you will attend talks from both academia and industry, learning about a wide variety of AI-related applications. After these talks, we will serve dinner and will hold interactive, coding workshops.
- Computer Vision for Breast Cancer Prediction from Histopathology Images.
- Deep Learning NLP Models for Retrieving Relevant arXiv Papers
Stella is a member of the Peltarion AI Research team working as a data scientist. She is a recent graduate of the Machine Learning Master’s programme at KTH. Her Thesis Project focused on improving multilingual Language Models for low resource languages and measuring Gender-Bias in contextualized embeddings. At Peltarion, she mainly works on research projects focusing on Natural Language Processing. She has a strong interest in Bias, Fairness and Explainability in AI, and is currently researching methods of measuring Gender Bias in Transformer Models.
Axel is an AI Research Engineer in Peltarion’s research team. A large part of Axel’s research has involved the use of deep learning for weather forecasting during which he has trained deep learning models achieving forecasts competitive with those produced by physical-based simulation models used in practice today. Axel has also worked with surgical image segmentation, neural architecture search and active learning for transformer-based models. Prior to his work at Peltarion, Axel studied the Machine Learning Programme at the Royal Institute of Technology in Stockholm and worked at GetCompliant AB as a machine learning and front-end developer.
Youssef is doctoral student at The Royal institute of technology (KTH) Sweden, specializes in perception systems and social artificial intelligence. His current research includes developing systems that are capable of detecting and classifying internal states (e.g. frustration, stress) using facial thermal signature and visual social cues. Youssef holds a masters degree in Robotics from the University of Bristol, UK of which he also worked on social robotics and developed a system that is able to detect if a person is being interactive within a group, by using the social signals of the surrounding group members.
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